specific steps in data modeling (1) conceptualize the user's view of data –what are the basic...
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Specific Steps in Data Modeling(1) Conceptualize the user's view of data
– what are the basic features needed to solve the problem?
(2) Select the geographic representation – points, lines, areas, rasters, TINs
(3) Define objects, features, and relationships – draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
( 1 ) User’s View of Data
( 1 ) User’s View of Data cont.
(2)Select
geographic rep.
Steps in Data Modeling(1) Conceptualize the user's view of data
– what are the basic features needed to solve the problem?
(2) Select the geographic representation – points, lines, areas, rasters, TINs
(3) Define objects and relationships – draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
Unified Modeling Language• Entity-relationship diagrams
• Design methodologies, diagram notations
• UML– Not a design methodology
– Just a diagrammatic notation based on methods
– Endorsed by leading software and database companies
• HTML
Unified Modeling LanguageUML
• Diagrammatic notation = “visual language”...
• For constructing a data model– Explains, documents on object-oriented structure
• Drawings, relationships constructed in Visio– Like CAD for Civil Engineering
• Tools to input a drawing to ArcGIS– input data to the data model
Basic UML Grammer
• Things– “Classes” sometimes grouped in “Packages”
• Relationships
• Diagrams
UML Things
UML NotationZeiler pp. 97-99
• a class is shown as a box
• top part contains the name of the class
• lower part contains the attributes
• methods associated with the class
• lines connect boxes and indicate relationships
UML Notation ( cont. )
• Abstract class – specify subclasses
underneath– Mammals w/human or
dog feature classes– no new instances
• Feature Class– Specify subtypes
underneath– Human, dog, cat
Example: Chicken Object Model
Graphic courtesy of Maidment et al., ArcHydro team
Objects and Features
• Object (real world)– in ArcGIS an object is non-spatial
– it is NOT a point, line, or area
– it has no geographic location
– it has no shape attribute in its table
– Drainage network, ship, vehicle, … customer, lake, house, etc.
• Feature (spatial context)– an object that has geographic location
– a point, line, area, TIN, raster
Relationships
• Links between classes, shown as lines
• One to one
• One to many
• Many to many
Relationships (cont.)
• 1:1 - solid line– one record in Class A linked to one record in
Class B• “is married to”• the class of state capitals linked to the class of
states
• 1:n - solid line with * at one end– one record in Class A linked to any number of
records in Class B• "owns" • the class of states linked to the class of area codes
Relationships (cont.)
• m:n - solid line with * at both ends– any number of records in Class A linked to any
number of records in Class B• "has visited”• "was never married to" • the class of mountain lions linked to the class of
wilderness areas
Graphic courtesy of Maidment et al., ArcHydro team
Type Inheritance
• White triangle• Class B inherits the
properties (attributes, methods) of Class A
• the class street inherits from the class transportation network
• Solid diamond• the parts and the whole
depend on each other
Graphic courtesy of Maidment et al., ArcHydro team
MDeviceIDEastNorthSpeedDirection112.110.88.6121111.312.57.922019.3-3.57.5130114.015.13.923417.312.09.1115
MeasuredData
InstantaneousPoint (ex: CTD)InstantaneousPoint (ex: CTD)
Measurement
XX
YY
TimeStampTimeStamp
MeasuringDevice
MDeviceIDNameTypeMeasurementID1Bob12Poncho13Juanita14Mia25Anita2
MeasuringDevice
MTypeIDVarNameVarDesc VarUnitsMDeviceID1Oranges12Bananas13Cubic cm24Rocks25Limes3MeasuredType
ZZ
MarineIDMarineCodeSeriesIDIPointTypeRecordedTime1AAA1105/04/58 12:00 002BBB1105/04/58 12:30 003CCC1105/04/58 13:00 00
InstantaneousPoints
MeasurementMeasureIDMarineIDZLocXlocYlocServiceTripSeviceDesc11-0.821-1.531-3.542-0.852-1.5
Michael Blongewicz
ArcMarine GeodatabaseOverall Geodatabase
Feature Class
Feature ClassFeature Dataset
Table
RelationshipClass
Steps in Data Modeling(1) Conceptualize the user's view of data
– what are the basic features needed to solve the problem?
(2) Select the geographic representation – points, lines, areas, rasters, TINs
(3) Define objects and relationships – draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
Data Model Levels
IncreasingAbstraction
RealityReality
Conceptual ModelConceptual Model
Logical ModelLogical Model
Physical ModelPhysical Model
Human-oriented
Computer-oriented
Real World Objects and relationships
DatabaseSchema
(Object state)
Physical Model
Modeling ProcessConceptual Model
Lists, flow diagrams, etc
Logical ModelDiagram in CASE
Tool
Graphic courtesy of ESRI
Steps in Data Modeling(1) Conceptualize the user's view of data
– what are the basic features needed to solve the problem?
(2) Select the geographic representation – points, lines, areas, rasters, TINs
(3) Define objects and relationships – draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data– e.g., Marine Data Model tutorial
Arc Marine Data Model Exercise
• Exercise and data at dusk.geo.orst.edu/djl/arcgis/ArcMarine_Tutorial/
• What to turn in:– Screen snapshot of what your ArcMap session looks like
at the end of Section 4 (including dynseg referencing)
– Answers to 2 simple questions at end of Section 4 (which cruise? which vehicle?)
– Can put all of the above in a single MS-Word document, labeled with your NAME please!
• Due in Dropbox, May 3rd, 6:00 p.m.
Gateway to the Literature• Arctur, D. and Zeiler, M., 2004, Designing Geodatabases, ESRI
Press• Lowe, J.W., 2003. Flexible data models strut the runway.
Geospatial Solutions, 13(2): 44-47.• Maidment, D.R., 2002. Arc Hydro: GIS for Water Resources,
ESRI Press, 203 pp. w/CD.• Li, X. and M.E. Hodgson, 2004. Vector field data model and
operations. GISci. Rem. Sens., 41(1): 1-24.• Wright, D., Blongewicz, M., Halpin, P., and Breman, J., A new
object-oriented data model for coasts, seas, and lakes, in Green, D.R. (ed.), Coastal and Marine Geospatial Technologies, London: Springer, in press. – dusk.geo.orst.edu/djl/arcgis/coastgis_book_final.pdf
• Wright, D.J., Halpin, P.N., Blongewicz, M.J., and Breman, J.B., Arc Marine: GIS for a Blue Planet, Redlands, CA: ESRI Press, in prep and review, due out 2006/7. – dusk.geo.orst.edu/djl/arcgis/book
Resulting Analysis - ArcHydro
From Arctur and Zeiler, Geodatabase Design, ESRI Press.